4.7 Article

Evaluation of distributed hydrologic impacts of temperature-index and energy-based snow models

期刊

ADVANCES IN WATER RESOURCES
卷 56, 期 -, 页码 77-89

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.advwatres.2013.03.006

关键词

Snow; Energy-balance; Temperature-index; Hydrologic model

资金

  1. Duke University
  2. NASA [NNX11AK35A]
  3. NSF [CBET-0838607]
  4. NSF-CBET [0854553]
  5. USDA-ARS CRIS Snow and Hydrologic Processes in the Intermountain West [5362-13610-008-00D]
  6. USDA-NRCS Water and Climate Center-Portland, Oregon [5362-13610-008-03R]
  7. USDA-ARS Headquarters Postdoctoral Research Associate Program [0101-88888-016-00D]
  8. USDA-NRCS Conservation Effects Assessment Project [5352-13610-009-14R]
  9. USDA-ARS CRIS Preserving water quality and availability for agriculture in the Lower Mississippi River Basin [7408-13000-024-00D]
  10. Div Of Chem, Bioeng, Env, & Transp Sys
  11. Directorate For Engineering [0854553] Funding Source: National Science Foundation
  12. NASA [143049, NNX11AK35A] Funding Source: Federal RePORTER

向作者/读者索取更多资源

Two commonly used strategies in modeling snowmelt are the energy balance and temperature-index methods. Here we evaluate the distributed hydrologic impacts of these two different snowmelt modeling strategies, each in conjunction with a physics-based hydrologic model (PIHM). Results illustrate that both the Isnobal energy-balance and calibrated temperature-index methods adequately reproduce snow depletion at the observation site. However, the models exhibit marked differences in the distribution of snowmelt. When combined with PIHM, both models capture streamflow reasonably during calibration year (WY06), but Isnobal model gives better streamflow results in the validation year (WY07). The uncalibrated temperature-index model predicts streamflow poorly in both years. Differences between distributed snowmelt, as predicted by Isnobal and calibrated temperature-index method, and its consequent effect on predicted hydrologic states suggest the need to carefully calibrate temperature-index models in both time and space. Combined physics-based snow and hydrologic models provide the best accuracy, while a temperature-index model using coefficients from the literature the poorest. (c) 2013 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据